Professor HeungKyu Lee received the 2014 Technology Innovation Award for his contributions to innovative research in the field of computer science. The 2014 Technology Innovation Award, given on December 15, 2014, offers 3,000,000 KRW to the awardee. Upon receiving the award, Professor Lee has donated 1,000,000 KRW to the KAIST CS department.
Congratulations！

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Research Team led by Professors Junehwa Song and I..

Research Team led by Professors Junehwa Song and Insik Shin developed a method that utilizes multiple smartphone speakers to produce 5.1-channel surround sound.
For the news article in Korean, please visit, http://www.hankyung.com/news/app/newsview.php?aid=2014123010377

At the 2014 Seoul Conference for Research using Public Data, the following paper from our department won third place in the Best Paper competition:
"Public Transportation Movement Pattern and Topic Analysis based on Topic Modeling"
by Ph.D Student Hosung Park and Professor Sue Moon.
Congratulations！

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Seung-Hwan Baek, MS student, and Prof. Min H. Kim ..

Seung-Hwan Baek, MS student, and Prof. Min H. Kim presented their work on 3D stereo imaging and received the Songde Ma Best Application Paper Award and the Best Demo Award simulateneously at the Asian Conference on Computer Vision (ACCV 2014).
Congratulations on the best paper awards at ACCV 2014.

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Hancom-KAIST Research Center Opening Ceremony

KAIST and Hancom have pledged to jointly collaborate in research and development of innovative technologies and solutions for software development.
The opening ceremony for Hancom-KAIST Research Center was held on October 29th, 2014 in the CS building, with President Steve Kang of KAIST, President Sang Chul Kim of Hancom and Vice-president Hong Goo Lee of Hancom in attendance.
KAIST and Hancom signed a memorandum of understanding (MOU) in April 2014 for research collaboration on software industry development. Since the signing of MOU, the two entities have held several important meetings to select five research projects and agreed to establish the Hancom-KAIST Research Center. In addition to carrying out the five projects, the Center plans to actively pursue new research projects.
President Steve Kang of KAIST said in his congratulatory remarks, “KAIST will provide every support necessary to make the Research Center a role model in industry-research collaboration as well as a leading contributor to the software industry development in Korea.” He also spoke of his plans beyond joint research collaboration, by pledging to support “joint workshops and research efforts in future trend analysis, and talent exchange between KAIST and Hancom.”
President Sang Chul Kim of Hancom said in his opening speech, “Through the newly established Research Center, Hancom and KAIST will collaborate closely and produce great synergetic effects in research and development.” Furthermore, he expressed his determination to, “make the Hancom-KAIST Research Center a ‘cradle of innovative software technologies’ and thus increase the competitiveness of software industry in Korea.”

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Francisco Rojas, PhD student, received the Disting..

KAIST Computer Science Ph.D. Student Francisco Arturo Rojas (http://mind.kaist.ac.kr/Francis) (age 32) who is advised by Professor Hyun S. Yang (http://mind.kaist.ac.kr/professor.php) since the spring of 2010 received the Distinguished Paper Award at the international CyberWorlds 2014 (http://www.cw2014.unican.es) conference which took place at the royal Magdalena Palace in Santander, Spain in October 6-8. He presented two full papers, and the paper that won the award was titled “Safe Navigation of Pedestrians in Social Groups in a Virtual Urban Environment”, which was additionally co-authored by the founder of PsyTech LLC (http://psychologicaltechnologies.com), Fernando Tarnogol, a licensed psychologist who with a hired team of developers created the city virtual environment with vehicular traffic for which the crowd simulation research work was applied. The crowd simulation featured in this paper is the most up-to-date extension of ongoing two-year research work at the Artificial Intelligence and Media Lab (http://mind.kaist.ac.kr/crowdsimulation.php) of KAIST in making non-playable virtual characters mimic how real people move together in real life in social formations, with previous versions published at conferences such as Computer Graphics International (CGI 2014) (http://rp-www.cs.usyd.edu.au/∼cgi14/program/papersessions.php) in Sydney, Virtual Reality Continuum and Its Applications in Industry (ACM SIGGRAPH VRCAI 2013) (http://www2.mae.cuhk.edu.hk/∼vrcai2013/program.html) in Hong Kong, and Computer Animation and Social Agents (CASA 2013) (http://www.cs.bilkent.edu.tr/∼casa2013/?p=schedulespeakers) in Istanbul. The crowd simulation realism results were positively evaluated by many individuals via the original Oculus Rift headset for developers.
Furthermore, the virtual reality application itself for which the research is applied, called PHOBOS (http://phobos.psychologicaltechnologies.com), is actually meant to be a professional exposure therapy tool to be used by doctors for the treatment of many patients’ common phobias and anxiety disorders, such as fear of heights, flying, public speaking, being confined in closed or small spaces, crowds, and spiders, among others. Since October 7 there has been a crowd funding campaign by PsyTech LLC at INDIEGOGO
(https://www.indiegogo.com/projects/phobos-anxiety-management-vr-platform) in order to continue development of the product which is currently in its early stages. So far the campaign has generated over ＄1300 for which Francisco himself is actually a stakeholder given his major research contribution to the project. The funding campaign will close on November 25 this year.

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SGLab and Boeing (USA) Sign Research Collaboration..

The Scalable Graphics Lab (SGLab) led by Professor Sungeui Yoon signed a collaboration agreement with Boeing for joint research on massive model rendering. This research collaboration is supported by a total ＄375K fund for two years.
For more information, visit: http://sglab.kaist.ac.kr/T-ReX/

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[Alumni] Dr. Sun-Hwa Hahn Appointed as the New Pre..

Dr. Sun-Hwa Hahn has been appointed as the new president of KISTI (Korea Institute of Science and Technology Information) on September 12, 2014. Dr. Hahn holds Bachelor of Science degrees in chemical engineering from Hanyang University and information engineering from SungKyunKwan University. After receiving her Master’s and Ph.D. degrees from the KAIST Computer Science department, she began working at KISTI in 1997 and served as the director of Knowledge Support Center and Information and SW Research Center. Starting January 2013, she has also held important leadership roles in the Association of Korean Woman Scientists & Engineers and Promotion Proclamation of the Citizens' Coalition for Scientific Society. We expect more success from her new role as the president of KISTI！

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Makao Talk： Undergraduate Student Spotlight

Donghwan Kim, Taesoon Jang, and Cheolho Jeon are the members of the team that placed first in the Kakao-KAIST Hackathon.
1) How did you get to join the Computer Science (CS) department?
Taesoon: I had my first programming experience after I came to KAIST and kept programming for fun. When it came time for me to declare my major, I chose CS over chemistry, mainly because I really enjoyed the CS101 course and the CS department info session.
Cheolho: I also had my first programming experience after I came to KAIST. In choosing my major, I knew I wanted to learn something that will be useful in the future and chose CS.
Donghwan: I had originally intended to major in electrical engineering, but I changed my mind and chose CS because I enjoyed programming. I like the logical thinking process involved in programming and seeing the end result in an executable program.
2) What was your academic path like up until joining the CS department?
Cheolho: I have an academic path that is different from most people here at KAIST. I attended junior high and high school in China and came here in the Spring of 2013. I remember I had a bit of hard time as a freshman while adjusting in the new setting.
Taesoon: I graduated from a science high school in two years, which is an academic path commonly found among my peers here at KAIST.
Donghwan: I graduated from Jang Young-Sil Science High School, which is where I first learned programming.
3) What was your childhood dream? What are you doing now to achieve that dream?
Taesoon: When I was really young, I wanted to become a scientist. After I grew older, I wanted to become an entrepreneur, retire early, and then explore the world. I gained some entrepreneurship experience while taking the last three semesters off, and I would like to try it again in the near future.
Donghwan: When I was young, I wanted to succeed, make a lot of money, and gain respect for my work. Now, instead of that kind of success, I want to do work that I can enjoy while collaborating with my friends.
Cheolho: My dream was to have fun in life while helping to make the world a better place to live. I am having fun in life now and I expect it will be so in the future. I believe there are many ways to make the world a better place from where I am, such as doing research and creating a useful service.
4) What are your strengths?
Taesoon: I work with a can-do spirit rather than fear of failure. Even if I do not know something well in the beginning, I have learned that confidence always leads to better end results.
Cheolho: I think my passionate attitude about work is my strongest point. I am passionately driven to complete any project that I started, though the end result sometimes turns out to be rather unexpected.
Donghwan: My strongest point is the ability to block out all the outside noise and sharply focus only on my work.
5) What are you passionately working on in the field of computer science these days?
Cheolho: I am working on building a strong foundation of CS knowledge by studying hard and working with other CS people.
Taesoon: I would like to get to know people of various backgrounds in our department, because they can become not only my friends but also coworkers someday！
Donghwan: I am constantly searching for what I want for my professional career. I try to participate in many different activities, and I am doing an internship this semester.
6) What values and future prospects do you see in your current work?
Taesoon: The interaction I get with different people in the CS department will prove to be valuable in the future. They are all very intelligent and highly likely to succeed, so I look forward to working with them after college.
Donghwan: My current internship is a great opportunity to explore my future career paths. Although I cannot measure its exact value, I am content and enjoying the internship as it is.
Cheolho: The value of my current work will depend on how well I get it done right now. Also, networking with a lot of CS people will prove valuable in my future life as well as career.
7) What were your happiest and most disappointing moments, respectively, in the CS department?
Donghwan: My happiest moment was when the project I worked on all night finally produced successful results. Any CS student can probably related to this moment of joy. My most disappointing moment was when I felt that course materials were too difficult even after trying hard to follow them.
Taesoon: I personally cannot think of the most disappointing moment. My happiest moment was when my ideas got accepted by others during a project brainstorming session.
Cheolho: My most disappointing moment was when the PA I worked for days failed. It consumed a lot of time and ruined the score in the end. I have had many happy moments so far, and the best one was successfully developing an application during Kakao-KAIST Hackathon.
8) What do you think is the best thing about studying computer science?
Taesoon: With even just a small bit of knowledge, there are so many ways to apply it and make a difference.
Cheolho: I think the ubiquitous nature of computing is the best thing – I will never go hungry as long as I have a laptop to work with.
Donghwan: CS is attractive because it has technologies with potentials to make the world a better place. It is much more accessible than other engineering disciplines, such as electrical engineering and bioengineering. By studying CS, one gains access to the power to change the world in a positive way.
9) What would you like to say to those interested in joining the CS department?
Donghwan: As Eric Schmidt once said, “If you’re offered a seat on a rocket ship, get on, don’t ask what seat.”
Cheolho: Mmm… CS is really fun. It doesn’t have to be a painful subject if you manage it well. I did not have any CS knowledge before entering KAIST, but I am doing fine now. The initial learning curve is not too high, so don’t be afraid to try！
Taesoon: Many people mistakenly assume that studying CS takes some special skills and give up before trying it out. If you enjoyed CS101, you should consider joining the CS department. I believe genuine interest in the subject is more important than special skills.
10) What are your future plans?
Taesoon: After graduating, I would like to get a job abroad or in Korea, become an entrepreneur, or go to graduate school.
Cheolho: I will go to graduate school or work in the industry. Until then, I would like to learn and experience as much as I can here at KAIST.
Donghwan: I will fulfill the military service requirement by going to graduate school or working in the industry. Afterwards, I would like to find career that will allow me to make a positive difference in the world.

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Artificial Intelligence and Machine Learning

[Prof. Kee-­Eung Kim]
The ultimate goal of artificial intelligence (AI), which is in essence building intelligent systems, requires computational and mathematical frameworks for intelligent behaviors. At the core of these frameworks lies the principle of rationality, and the decision theory provides a classical but effective tool for building intelligent systems as well as understanding the behavior of humans and animals. My research group at KAIST has been devoted to designing and developing decision-theoretic representations and algorithms for AI.
Research Results
My research group is working on representations and algorithms for decision theoretic planning problems, including large scale Markov decision processes (MDPs) and partially observable MDPs (POMDPs). Decision theory is one of the most important approaches to understanding and implementing the rational and intelligent behavior.
1. MDPs and POMDPs
The classical MDP/POMDP representation has been a useful tool for modeling intelligent behaviors for decades. However, we often encounter the need to extend the standard representation to effectively capture real-world problems. For example, how can we naturally specify the constraints on the properties of desired solutions, or handle the uncertainty in the parameters of the model? As we extend the standard model, how can we address the computational challenges in designing efficient algorithms? We have addressed some of these theoretical issues and presented at top-tier AI conferences.
2. Machine learning of behavioral data
The standard way of machine learning for the intelligent behavior is the reinforcement learning (RL). However, the standard setting in RL algorithms assumes prescribed reward functions, which is not an easy task to specify them in practice. Inferring the reward function from the behavior data is referred to as the inverse reinforcement learning (IRL), and its significance has emerged from the connection among RL and other disciplines such as neurophysiology, behavioral neuroscience, and economics. IRL is an important problem for understanding human and animal behaviors, and we have presented our algorithms at a top-tier machine learning conference and journal.
3. Applications
Besides theoretical research on representations and algorithms, our group also worked on applications to demonstrate the usefulness of the decision-theoretic AI approach. Our work on applications include spoken dialogue systems and brain-computer interface systems.
Awards
1. 2nd place in the POMDP track of the International Probabilistic Planning Competition (IPPC), 2011
2. Best poster award at the Pacific-Rim Conference on Artificial Intelligence (PRICAI), 2010
References
Published papers
1. Jaedeug Choi and Kee-Eung Kim,“MAP Inference for Bayesian Inverse Reinforcement Learning”In: Proceedings of Neural Information Processing Systems (NIPS 2011). [Accepted]
2. Jaeyoung Park, Kee-Eung Kim, and Yoon-Kyu Song,“A POMDP-based Optimal Control of P300-based Brain-Computer Interfaces”In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) NECTAR Track. 2011. [8th Korean AAAI paper]
3. Dongho Kim, Jaesong Lee, Kee-Eung Kim, and Pascal Poupart,“Point-Based Value Iteration for Constrained POMDPs”In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). 2011. [5th Korean IJCAI paper]
4. Eunsoo Oh and Kee-Eung Kim,“A Geometric Traversal Algorithm for Reward-Uncertain MDPs”In: Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI). 2011. [1st Korean UAI paper]
5. Pascal Poupart, Kee-Eung Kim, and Dongho Kim,“Closing the Gap: Towards Provably Optimal POMDP Solutions”In: Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS). 2011. [1st Korean ICAPS paper]
6. Jaedeug Choi and Kee-Eung Kim,“Inverse Reinforcement Learning in Partially Observable Environments”Journal of Machine Learning Research (JMLR), 12. 2011. [2nd Korean JMLR paper]
7. Dongho Kim, Jin Hyung Kim, and Kee-Eung Kim,“Robust Performance Evaluation of POMDP-Based Dialogue Systems”IEEE Transactions on Audio, Speech, and Language Processing (TASLP), 19(4). 2011.
8. Youngwook Kim and Kee-Eung Kim,“Point-Based Bounded Policy Iteration for Decentralized POMDPs”In: Proceedings of Pacific-Rim Conference on Artificial Intelligence (PRICAI) / Lecture Notes in Computer Science (LNCS) 6230. 2010. [Best poster award]
9. Jaeyoung Park, Kee-Eung Kim, and Sungho Jo,“A POMDP Approach to P300-Based Brain-Computer Interfaces”In: Proceedings of the ACM International Conference on Intelligent User Interfaces (IUI). 2010.
10. U.S. Patent Application 20110152710,“Adaptive Brain-Computer Interface Device”

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Developing a hyperspectral 3D imaging system and s..

[Prof. Min H. Kim]
3D imaging techniques have been broadly used in manufacturing, entertainment and military industries. However, current 3D imaging systems have been limited to capturing and representing only trichromatic 3D objects. This research project extends the spectral dimension of 3D imaging techniques beyond the trichromatic spectrum. It is the first approach to build a complete 3D scanning system that measures the hyperspectral reflectance of solid objects. This research project includes the design and building of a 3D imaging system, the development of 3D imaging algorithms, and several 3D software applications to visualize such hyperspectral 3D image data. The research outcome of this project could be broadly adapted to physically meaningful measurements of hyperspectral material appearance of 3D solid objects in natural science and bio-medical engineering.
Schematic overview of the 3D imaging spectroscopy system (ACM Trans. on Graphics, 31(4), 38:1-11, SIGGRAPH 2012)
Research Funding
ㆍ This work was supported by the National Research Foundation (NRF) of Korea, Samsung Electronics and Microsoft Research Asia additionally.
Research Results
ㆍ This imaging system was introduced for the first time in ACM Transactions on Graphics, 2012, the top journal in computer graphics. The associated visualization software application was published in ACM Journal on Computing and Cultural Heritage, 2014 such that this work was received a best paper award in 2012 at the International Symposium on Virtual Reality, Archaeology and Cultural Heritage (VAST 2012).
References
ㆍ M. H. Kim, T. A. Harvey ,D. S. Kittle, H. Rushmeier, J. Dorsey, R. O. Prum, D. J. Brady (2012), "3D Imaging Spectroscopy for Measuring Hyperspectral Patterns on Solid Objects," ACM Transactions on Graphics (Proc. SIGGRAPH 2012), 31(4), July 2012, pp. 38:1-11 (IF=3.361)
ㆍ M. H. Kim, H. Rushmeier, J. ffrench, I. Passeri, D. Tidmarsh (2014), "Hyper3D: 3D Graphics Software for Examining Cultural Artifacts," ACM Journal on Computing and Cultural Heritage, 7(3), February, pp. 1:1-19

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Analysis on Media Characteristics of Twitter

[Prof. Sue Bok Moon]
Via quantitative analysis with the not-sampled, but complete data, we show media-like characteristics of Twitter. Online communication has emerged as a new form of media, and our work is one of the first to demonstrate a quantitative approach for new media research.
Research Results
Online Social Network (OSN) services are creating a sea of new products and services based on the social networks. OSN services, such as Facebook and Twitter, threaten the established ones, such as Microsoft, Google and Apple. Twitter, a microblogging service, stands out from other OSN services in that its relations are directional and most user profiles and tweets are public. For three months from June 2009, we collected profiles of all Twitter users. Our analysis shows that Twitter has characteristics of not only a social network but also of media. The reciprocity typically over 80％ in social networks is low (less than 50％). Most tweets are of news nature. Retweets expand readership by 100 or more easily.
※Excellency and Expected effects
No further explanation is necessary for the influential power of Twitter, as demonstrated in the recent Seoul mayor election. However, in 2009 when we started our research on Twitter, domestic awareness was low and nobody could have imagined the explosive power in the MENA (Middle East North Africa) situations this spring. Our paper, “What is Twitter, a Social Network or a News Media?” published in the World-Wide Web (WWW) conference on April 2010, investigates social phenomena via Twitter and provides statistical approaches on the complete data of Twitter. Our data crawling and analysis methodologies have become a de-facto standard in follow-up research. The Library of Congress in US has decided to archive the entire Twitter data, thus acknowledging the historic significance of massive-scale communication records among hundreds of million users for the first time in human history. Twitter provides an epoch-making data that allows people to collect information and observe its diffusion in an unprecedentedly massive scale and is changing the face of research methodologies in computer science, sociology, politics, business administration, cognitive science and more.
Our paper, published in the WWW conference in 2010, is cited more than 2000 times (via Google Scholar) as of July 2014 and we expect the number to increase even more in the coming years. This work has been covered by domestic and foreign press such as ChosunIlbo, HankookIlbo, MIT Technology Review Blog, ReadWriteWeb, the Observer, PC World, Mashable Op-Ed. Computer science graduate courses at Georgia Institute of Technology, UC Santa Barbara and Cornell have included our paper in their lecture material. Non-computer science departments, such as MIT Business School, Bowdoin College sociology department, and the University of California at San Diego Visual Arts Department have also included our work. From 2009 I have given more than 10 invited talks on this paper, including Boston Univ., Northwestern Univ., UC Santa Barbara, Microsoft Research Bangalore, Microsoft Research Redmond, Duke Univ., North Carolina State Univ.
This work provides data collection and analysis methodologies for new media studies and falls to the category of fundamental science. It is hard to file for a patent or apply immediate productization from this work but this work reveals basic characteristics of new media, of which knowledge is imperative to designing derivative products or services. Our investigation of human society via online service provides a new direction for interdisciplinary research between computer science, humanities, and social sciences. KAIST established the Web Science and Technology division under the World-Class University program sponsored by the Ministry of Education, Science and Technology, for this kind of interdisciplinary research. In Korea with its world-best high-speed Internet infrastructure and less-than-1％ illiteracy and highly educated work-force, interdisciplinary research could be the guiding light to take our IT industry to the next level. We hope our social network of interdisciplinary collaborators initiated by this Twitter research continues to expand and become a catalyst for explosive growth in our academic excellence.
Reference
Published papers
1. Haewoon Kwak, Changhyun Lee, Hyunwoo Chun, Sue Moon,“What is Twitter, a Social Network or a News Media?” Proceedings of the World-Wide Web, April 2010, Raleigh, North Carolina.(Acceptance rate: 14％ , Citation: 313)
Funding Sources
1. Collect, Analyze and Share for Future Internet : High-Precision Measurement and Analysis Research, 2008.3.1.∼2013.2.28., MKE

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Scalable Big Graph Mining

[Prof. U Kang]
Scalable big graph mining using distributed systems opens new opportunities for the discovery of interesting patterns and anomalies on very large graphs which could not be analyzed before.
Article:
Graphs are ubiquitous: computer networks, social networks, mobile call networks, biological networks, citation networks, protein regulation networks, and the World Wide Web, to name a few. Spurred by the lower cost of disk storage, the success of social networking sites (e.g. Facebook, Twitter, and Google＋) and Web 2.0 applications, and the high availability of data sources, graph data are being generated at an unparalleled rate. They are now measured in terabytes and heading toward petabytes, with more than billions of nodes and edges.
Mining such big graphs helps us find patterns and anomalies which lead to many interesting applications including fraud detection, cyber security, social network analysis, etc. The research team at Prof. U Kang in Department of Computer Science is working on scalable big graph mining which includes two components: scalable algorithms and discoveries on real world graphs.
Scalable Algorithms. Traditional graph algorithms assume the input graph fits in the memory or disks of a single machine. However, the recent growth of the sizes in graphs violates this assumption. Since single machine algorithms are not tractable for handling big graphs, the research team at Prof. U Kang is working on designing and developing scalable algorithms and distributed platforms for mining and managing big graphs. Prof. U Kang is the main author of the award-winning Pegasus graph mining software which includes various large scale graph mining algorithms including PageRank, Random Walk with Restart (RWR), diameter estimation, connected components, eigensolver, and tensor analysis.
Discoveries on Real World Graphs. The developed scalable algorithms lead to the analysis of large real world graphs, and interesting discoveries of patterns and anomalies which could not be found before. One of the most interesting discoveries is the seven-degrees of separation in one of the largest publicly available Web graphs with ∼7 billion edges. The discovery suggests that the so-called ＇small world' phenomenon exists in the Web, and the distance between any two Web pages is much smaller than people's expectations. Another interesting discovery is the existence of suspicious adult advertisers in the Twitter who-follows-whom social network at 2009 with 3 billion edges. In the scatter plot of degree vs. triangles of Twitter accounts, some famous U.S. politicians have mildly connected followers, while adult advertisers have tightly connected followers, creating many triangles. The reason is that adult accounts are often from the same provider, and the accounts follow each other to boost their rankings, thereby creating many cliques containing triangles.
Image caption:
Anomaly detection in graph: the degree vs. triangles in the Twitter who-follows-whom social network at 2009. Some famous U.S. politicians have mildly connected followers, while adult advertisers have tightly connected followers, creating many triangles. The reason is that adult accounts are often from the same provider, and the accounts follow each other to boost their rankings, thereby creating many cliques containing triangles. [U KANG AND CHRISTOS FALOUTSOS, BIG GRAPH MINING: ALGORITHMS AND DISCOVERIES, SIGKDD EXPLORATION VOLUME 14 ISSUE 2, DECEMBER 2012.

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Smartphone-based Interaction Sensing to Innovate O..

[Prof. Junehwa Song]
Advancing our smartphones as conversational interaction sensing platforms to promote social health in everyday life
Article:
A team of researchers in Dept. of Computer Science, KAIST are leading new mobile initiatives to build social context platforms and create life-immersive social services. The key inspiration is to advance our commodity mobile devices such as smartphones towards a face-to-face social gateway – to acquire the real-time social contexts and create proactive services naturally overlaid on our everyday face-to-face social lives. Why social? Because it is an integral basis which constitutes many of our daily activities, such as family life, team-oriented works, hanging out with friends, and so on. They believe that stretching out for diverse social contexts around the user will realize the foundation of future mobile systems which achieve holistic understanding on the user’s need and useful life-immersive services.
The quest begins with a question, “What would be the primitive context in our face-to-face social interaction?” As the initial and natural step, the research team focused on conversation, which would be the most prevalent tool to communicate with people just in front of us. A number of new technical challenges arises to recognize delicate conversational contexts with commodity mobile devices.
In 2013, they reached the first milestone, SocioPhone, a mobile face-to-face interaction platform with highlights meta-linguistic contexts in conversations. SocioPhone is described in a paper published in ACM MobiSys 20131 (International Conference on Mobile Systems, Applications, and Services) by a team of a KAIST graduate Youngki Lee, who is now an assistant professor of Information Systems, Singapore Management University (SMU), and 8 others. SocioPhone abstracts on-going conversations as a sequence of turns and pauses. SocioPhone provides applications with a set of intuitive APIs to monitor rich meta-linguistic context on the fly, without requiring computation-intensive semantic inference on conversation contents. At its core, the SocioPhone runtime monitors conversational turn-centric contexts in a highly-efficient and precise manner based on a new socially-leveraged collaborative sensing scheme. In addition to the paper publication, a live demonstration of SocioPhone won the Best Demonstration Award in ACM HotMobile 20132 (International Workshop on Mobile Computing Systems and Applications), which was conducted by a KAIST graduate student Chulhong Min and 14 others.
Continuing the efforts, the research team is now creating compelling applications which are indispensable for a new platform to find its unique values. Notably, they proposed TalkBetter, a prominent initiative for everyday clinical care applications. The paper describing TalkBetter has won the Best Paper Award in ACM CSCW 20143 (International Conference on Computer Supported Cooperative Work and Social Computing), which was authored by an interdisciplinary team of a KAIST graduate Inseok Hwang who is now a research assistant professor of Center for Mobile SW Platform in KAIST, Prof. Dongsun Yim in Dept. of Communication Disorders, Ewha Womans University, and 5 others. They introduced a mobile in-situ intervention service to expedite everyday family-driven care for children with speech impediments. With close collaboration with the speech-language pathologists and the patients regularly taking speech-language care, TalkBetter has been designed and developed as an integrated therapeutic service which facilitates the parents to acquire clinically desirable conversation habits throughout natural conversations, not only depending on simple a-priori prescription as it has been done thus far.
Today, many people observe growing concerns about the anti-social effects of smartphones, attempting to suppress the smartphone use in face-to-face social situations. These researches advocate an antithesis of such technophobic skepticisms. They are pursuing the pro-social potential of pervasive mobile devices around us, and realizing the first-of-its-kind mobile systems to enhance our everyday social life experience.
These researches were supported by National Research Foundation funded by Ministry of Science, ICT, and Future Planning (MSIP) and IT R&D Program of MSIP/KEIT of the Korean Government.
1. Lee, Y., Min, C., Hwang, C., Lee, J., Hwang, I., Ju, Y., Yoo, C., Moon, M., Lee, U., Song, J. SocioPhone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion. ACM MobiSys 2013, Taipei, Taiwan, June 2013.
2. Min, C., Hwang, I., Lee, J., Hwang, C., Yoo, C., Moon, M., Park, T., Lee, C., Lee, H., Kim, Y., Ju, Y., Lee, Y., Lee, U., Song, J. Demo: Bringing In-situ Awareness to Mobile Systems: Everyday Interaction Monitoring and Its Applications. ACM HotMobile 2013 (Demo), Jekyll Island, GA, USA, February 2013.
3. Hwang, I., Yoo, C., Hwang, C., Yim, D., Lee, Y., Min, C., Kim, J., Song, J. TalkBetter: Family-driven Mobile Intervention Care for Children with Language Delay. ACM CSCW 2014, Baltimore, MD, USA, February 2014.
Image caption:
Real-time meta-linguistic monitoring and feedback by the smartphone for the on-going conversation between the mother and her son. [PHOTO COURTESY OF THE RESEARCHERS]
Image caption:
Face-to-face conversation situations and socially-leveraged collaborative sensing scheme for conversational turn monitoring [PHOTO COURTESY OF THE RESEARCHERS]

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Virtual Reality-based Dental Training Simulator

[Prof. Jinah Park]
Dental caries and calculus are prevalent diseases among people. For better treatment of these diseases, dental students need to receive training efficiently and their skills must be assessed by standardized methods. Our research allows students to assess their skill based on the training results and provide an effective practice to master their skills. A novel collision model is developed to deal with various interactions between different shaped instruments and the oral cavity. The instrument is represented by a distance field and a set of points, and the tooth is represented as a distance field. The distance field of the tooth is updated by tracing the plastic deformation of tooth while the collision detection and the reflected force are efficiently computed from the distance field of the tooth and the set of points.
Research Results
1. A collision model for real-time simulation of tooth preparation
Since instruments for tooth cutting are small and sharp compared to the tooth, it is necessary to not only elaborate but also refine the collision model that handles the plastic deformation of the tooth caused by cutting instruments. To address this issue, we propose a real-time collision model in which the tooth is represented as a volume model with a distance field. This volume model is shared by not only a procedure to visualize the shape deformation of the tooth but also a procedure to detect collision and compute feedback force for haptic rendering. Our method can handle more than 10,000 volume elements within 1kHz, there is no limit on the shape of the instruments.
2. Adhesion attenuation model for dental calculus removal
In contrast to the hand scaling, the ultrasonic scaling delivers ultrasonic wave energy to the dental calculus to remove it by reducing the adhesion between dental calculus and tooth surface. To simulate this characteristic, we propose an adhesion attenuation model that reduces the dental calculus adhesion by the amount of wave energy inversely proportional to the distance squared from collided voxel. Our method enables the users to use the ultrasonic scaler in the advisable way.
3. VR-based dental simulator
Dental simulation ran on a personal computer with Core2Duo 3GHz central processing unit, NVIDIA Quadro FX 3700 graphics card, and 4 GB Ram. A Phantom Desktop was used to display the haptic feedback. Moreover, an immersive workbench, SenseGraphics Display 300, was used to align the hand-eye coordination. Our simulator provides different training scenarios: impacted wisdom tooth surgery, dental cavity preparation, ultrasonic scaling as shown in the Figure 1-3.
Excellency and Expected effects
Most of the previously developed dental simulations consider only a spherically shaped tool due to its simplicity in collision detection. Our collision model can handle any arbitrarily shaped instruments with multiple contacts between the instrument and the tooth. Moreover, synchronization between a visual model and a collision model is not required because our method resolves volume cut, multiple contacts, and feedback force within a haptic rate. The collision model can be applied to not only a bone surgery simulation but also a virtual sculpting simulation.

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Internet of things and system software

[Prof. Dae Young Kim]
The term Internet of Things was firstly introduced in 1999 by Kevin Ashton at the Auto-ID Labs, MIT, which is the primary research partner of GS1. GS1 is a global organization which provides various types of codes such as bar code, RFID code, QR code for thing identification, and also standardizing system infrastructure for global business and application. Among seven Auto-ID Labs (MIT, Cambridge, ETH Zurich, Keio, Fudan, Adelaide, KAIST) over the world, Auto-ID Lab, KAIST have studied in IoT field since 2002, with the RFID and wireless sensor network technology. And since 2005, we started to develop various IoT technologies that are specialized to GS1 standard. We are currently working on following projects; Oliot (GS1 based IoT Infrastructure Platform), SNAIL (6LoWPAN based IoT Connectivity Platform), SeaHaven (Visual Sensor Network Cloud Platform), IoT-App Ecosystem (Ecosystem for Mobile Versatile Applications), GPGPU HPC Cloud (Cloud Computing for HPC with GPGPU).
[Research Results]
The IoT is the vision that aims to give every day object virtual personality. The rationale behind this is to let them have global identification, computation and communication capabilities. That is, our everyday things become intelligent and are able to provide us with any information about themselves. As a result, vast opportunities to create entirely new dimension of services appear. In this regard, we have developed the following five technologies to realize the IoT vision.
(1) SNAIL: We enabled communication among things over Internet to achieve 6LoWPAN IoT network. SNAIL (Sensor Network for an All-IP World) is a solution for IoT network, which is a tiny IPv6-based sensor networking platform including a complete architecture of a lightweight TCP/IP stack supporting IPv6 adaptation, ad-hoc routing, header compression, and bootstrapping as well as four important technologies, mobility, web enablement, time synchronization, and security.
(2) Oliot: Oliot is aiming an international standard based IoT Infrastructure Platform, by extending the code system of GS1 and their standard architecture to support various IoT connectivity and protocols such as bar code, RFID, ZigBee, 6LoWPAN, etc. Oliot also aims a complete implementation of GS1/EPCglobal standard.
(3) IoT-App Ecosystem: IoT-App Ecosystem is a new ecosystem for mobile software, which enables easier interaction between mobile application and various smart things. This is currently being implemented for Android and supports current Android development environment.
(4) SeaHaven: SeaHaven is a portable and secure multi-tenant visual sensor networks cloud platform which covers visual sensor node operating systems, visual sensor streaming service, visual big data processing service, and user applications. The major goal of this project is to make the machine understand the context of the scene by leveraging visual sensors all over the world which are very beyond human’ visual sensory.
(5) GPGPU HPC Cloud: This project is about Cloud computing for HPC with general purpose graphical processing unit (GPGPU). Using GPGPU on Cloud will reduce cost and power usage than using only CPUs. We implemented platform with OpenStack, KVM, and API forwarding technique.
[Excellency and Expected effects]
(1) SNAIL: We make an effort to support secure, dynamic, global, and easy access to everyday objects using IPv6 address. Our IoT platform SNAIL is evaluated as a promising IoT platform and new version SNAIL 2.0 will come out soon.
(2) Oliot: The entire source code was opened to public and is designated to be utilized on various project such as EU IoT6 Smart Building Project, KAIST Dr. M Project, c-ITRC Food Safety System, Stanford Civil Engineering Project, Korea University Hospital Project, and Smart Consumer Electronics. The roadmap and vision of Oliot project is described in oliot.org.
(3) IoT-App Ecosystem: With this work, mobile application developers can more easily implement applications which interacts with pervasive smart things. Also, it aids the developers to publish their business logic to customers.
(4) SeaHaven: To make the machine understand the context of an event is a quite challenging job to handle. Variety and sparse distribution of sensors must be the most helping key in resolving this issue. SeaHaven provides a universal interface for sensors to cover variety and heterogeneity of sensor devices and a very scalable service architecture to easily scale out the system over the cloud infrastructure.
(5) GPGPU HPC Cloud: To use GPGPU on Cloud, previous approach only supports one to one mapping virtual machine and GPGPU. With API forwarding technique and Kepler architecture GPGPU, our platform supports scalable use of GPUs. And with efficient GPU resource scheduling algorithms, our platform can maximize resource utilization while providing SLA for HPC users.

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Investigating Reliable Computing Systems in Nano-s..

[Prof. Soontae Kim]
With technology scaling, feature sizes, and supply and sub-threshold voltages are decreasing for high performance, high transistor density, and low power consumption. At the same time, microprocessors and memory systems are integrating more transistors to extract more performance. Unfortunately, these trends make computing systems more susceptible to various errors. Transient errors occur when energetic neutrons coming from deep space and alpha particles from packaging materials hit transistors, which change the state of memory bits or the output of combinational logic temporarily. In addition, permanent errors due to process variations and wear-out in interconnect and transistors increase over time, which in turn decrease yield and lifetime of the computing systems. Therefore, it is essential to provide reliable computing on top of unreliable systems for the continued success of computing. We investigate low-cost processor architectures, memory systems and software to combat against those various errors in nano-scale era.
[Research Highlight]
Access-time Variation Insensitive Level-1 Caches [1]
Ever-scaling process technology increases variations in transistors. The process variations cause large fluctuations in the access times of SRAM cells. Caches made of those SRAM cells cannot be accessed within the target clock cycle time, which reduces yield of processors. To combat these access time failures in caches, many schemes have been proposed, which are, however, limited in their coverage and do not scale well at high failure rates. We proposed a new level-1 cache architecture (AVICA) employing asymmetric pipelining and pseudo multi-banking. Asymmetric pipelining eliminates all access time failures in L1 caches. Pseudo multi-banking minimizes the performance impact of asymmetric pipelining. For further performance improvement, architectural techniques were proposed.
[Reference]
1. Seokin Hong and Soontae Kim. AVICA: An Access-time Variation Insensitive L1 Cache Architecture. Design Automation and Test in Europe Conference (DATE’13), March 18∼22, 2013, Grenoble, France (Best Paper Award).

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OncoSearch： A web tool that searches biomedical li..

[Prof. Jong Cheol Park]
OncoSearch (http://oncosearch.biopathway.org) is a web tool that allows the user to query into biomedical literature for information on cancer-related genes and shows the results for further insights into oncogenesis, with an aim to catalyze and accelerate the ongoing cancer research.
[Article]
Automatic identification of gene-cancer relations from a very large volume of biomedical text is an important task for cancer research since changes in genes are known to be the main cause of oncogenesis and a huge amount of information on such genes is archived in biomedical literature databases. To identify such relations, it is essential to understand, as much as possible, how a gene affects a cancer and to distinguish oncogenes (genes that cause cancers), tumor suppressor genes (genes that protect cells from cancers), and biomarkers (genes that indicate normal or cancerous states) since this will speed up the development of treatment and diagnosis methods for cancer. Although genes may sometimes be explicitly claimed as oncogenes or tumor suppressor genes in the biomedical text, it is more often the case that information on gene-cancer relations is conveyed only implicitly with detailed descriptions about gene and cancer properties. Consider the example of the sentence below.
WWOX overexpression induced apoptosis and suppressed prostate cancer growth in vitro and in vivo [PMID:17704139].
While the gene WWOX is a well-known tumor suppressor, the sentence above does not contain an explicit reference to the gene as such. Instead, the sentence gives information that helps to classify the gene WWOX as a tumor suppressor of prostate cancer through the following inference: 1) WWOX expression level is increased, 2) prostate cancer regresses when WWOX expression increases, and 3) there is causality between the change in WWOX and the change in prostate cancer. By combining the three pieces of information above, one may classify the gene WWOX as a tumor suppressor gene. Although a single sentence with such implicit information may not provide enough evidence to confirm a particular gene's class, collecting a large amount of such information in the literature would certainly help to substantiate such a conclusion.
Prof. Jong C. Park’s research team at KAIST developed OncoSearch, a web tool that allows the user to query into the biomedical literature for free-text information on cancer-related genes and provides the results for further insights into oncogenesis, or the process by which normal cells are transformed into cancer cells. In particular, OncoSearch can classify genes into either oncogenes, tumor suppressor genes, or biomarkers by taking into account implicit information as well as explicit information on their roles. The tool characterizes gene-cancer relations described in biomedical text with 1) how a gene changes, 2) how a cancer changes, and 3) the causality between the gene and the cancer, and the tool infers the respective roles of genes in cancers. Through this classification, the research team showed that the tool can correctly pick out oncogenes and tumor suppressor genes already registered as such in biology databases. The research team also showed that only small portions, or 6.87％ and 3.76％, respectively, of the oncogenes and tumor suppressor genes in one of the de facto standard gene databases, or UniProtKB, are registered in the list of oncogenes and tumor suppressor genes published by Vogelstein and colleagues (Science, 2013). This indicates either 1) that the process of identifying new oncogenes or tumor suppressor genes is still at an early stage or 2) that the exact definitions of oncogene and tumor suppressor gene are highly dependent upon each biology database. OncoSearch is, thus, expected to catalyze much further research in oncology since the tool can collect and infer information about novel oncogenes, tumor suppressor genes, and biomarkers from the rapidly growing body of the literature that does not necessarily contain explicit expressions such as oncogene and tumor suppressor gene.

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High-physicality touch interfaces

[Prof. Geehyuk Lee]
Touch interfaces are now a de facto standard for information appliances. They enabled more direct and natural interaction than traditional computer interfaces, but are still in their early stage as the types of operations are quite limited compared with diverse surface operations that we perform in the real world. The limitations of the current touch interfaces stem mainly from their inability to discriminate touches of different degrees, for example, hover, light touch and heavy touch. We are interested in new possibilities that may be enabled when touch surfaces become more physically sensitive, for instance, when they can sense the approach or the pressure of the fingers as well as their touch. We are conducting a series of interaction design studies with high-fidelity prototyping, and are publishing some of early results in leading HCI conferences.
Research Results
Touch with Hover We developed a world-best class optical hover tracking touchpad technology and are exploring the potential of using it. Using this technology, we can provide a touch-screen-like interaction in the TV environment. For instance, the shadow of the user's fingers touches the screen, presses a button, and flicks a cover-flow-like list, while the fingers stay and move on a touchpad. In order to explore this concept, we developed a hover-tracking optical touchpad, and designed a TV application to demonstrate possible new interaction techniques. Through a prototyping study, we could correct some of our false expectations, and verify its potential as a viable option for a TV remote interface.
(left) RemoteTouch concept and device, (right) Hover-tracking long touchpad
Touch with Force The same finger movement on an object may be associated with different intentions depending on its normal and tangential forces. For instance, the same finger movement can be intended to turn a single page or to turn multiple pages, or to slide on a page, but a touch screen cannot differentiate these gestures. We solved this problem with a touch screen that can sense not only touch positions but also touch forces. We implemented a prototype device that can sense the normal and the tangential component of the forces on the screen, designed Force Gestures, which differ in terms of both touch movements and force patterns, and conducted an experiment to verify the feasibility of this approach.
(left) example force gestures, (right) example multi-point tangential force interaction
Excellency and Expected effects
A complete report of our research on the RemoteTouch concept was presented at ACM CHI 2011 [C1]. The CHI paper soon attracted the attention of technology reporters and a news article about the paper appeared in DiscoveryNews [W1] and MSNBC.com [W2]. The optical hover-tracking technology was also implemented into form factors of a standard laptop touchpad and long shaped palm rest-length touchpad, and presented at ACM UIST 2011 [C2] and ACM CHI 2013 [C3], as a demo and a poster, respectively. The long touchpad was also introduced by American technology blogs, NewScientist Blog [W3] and Gizmodo [W4]. Regarding Force-sensing touch technology, a complete report is presented at ACM UIST 2011 [C4] and ACM CHI 2013 [C5], which is one of the most competitive venues for UI researchers. Published at ACM CHI and ACM UIST, the results of the current research were verified to be original and academically important. The research is also expected to have an impact on ICT industry since their main application targets are smart phones and smart TVs. After the introduction of iPhone, mobile phone manufacturers realized the importance of UI technologies and are experimenting with many new UI technologies to impress the market. High physicality touch screen or touchpad as demonstrated by our research results is certainly one of them. We were invited to present our research on touch interfaces by major companies such as LG and Samsung this year. We could also attract research funds from an industry source [F1] and a government source [F2] for the current research. The aforementioned news articles [W1, W2, W3] also reflect the public interests in the current research.
References
C1. Sangwon Choi, Jaehyun Han, Geehyuk Lee, Narae Lee, and Woohun Lee, RemoteTouch: Touch-Screen-like Interaction in the TV Viewing Environment, CHI 2011 (paper).
C2. Sangwon Choi, Jaehyun Han, Sunjun Kim, Seongkook Heo, and Geehyuk Lee, ThickPad: A Hover-Tracking Touchpad for a Laptop, ACM UIST 2011 (demo).
C3. Jiseong Gu, Seongkook Heo, Jaehyun Han, Sunjun Kim, and Geehyuk Lee, LongPad: a touchpad using the entire area below the keyboard of a laptop computer, ACM CHI 2013 (paper)
C4. Seongkook Heo and Geehyuk Lee, Force gestures: augmenting touch screen gestures with normal and tangential forces, ACM UIST 2011 (paper).
C5. Seongkook Heo and Geehyuk Lee, Indirect shear force estimation for multi-point shear force operations, ACM CHI 2013 (paper)
W1. http://news.discovery.com/tech/shadow-remote- touchscreen-110519.html
W2. http://www.msnbc.msn.com/id/43095028
W3. http://www.newscientist.com/blogs/onepercent/2013/01/trackpad-ignores-accidental-to.html?cmpid=RSS％7CNSNS％7C2012-GLOBAL％7Conline-news
W4. http://gizmodo.com/5982160/intelligent-keyboard-wide-touchpad-is-smart-enough-to-ignore-your-palms
Funding Sources
1. Implementation of USN Sensor Platform and Network Systems, Funded by National Research Laboratory (NRL) Program of NRF, 2007-current
2. u-Agriculture, Funded by ITRC (Information Technology Research Center) Program of MKE, 2007-current

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Jaepil Huh, Student Spotlight

1) How did you get to join the Computer Science (CS) department?
My high school friends who graduated before me significantly influenced my decision to join the CS department. I graduated from a science high school, where the curriculum was much focused on subjects such as math, chemistry, physics, biology, astronomy, and CS. I personally found CS to be most attractive, because it allowed me to study at a more flexible pace and use the computer during studying hours. Whenever I got lost in my studies, my upperclassmen friends were there to help me get back on the right track. I was especially lucky to meet one friend, who took the time to pass on his knowledge of fundamental algorithms and problem solving skills. I cannot forget the joy of learning CS concepts from my friends in the winter of 2013, a year from which I chose to join the CS department.
2) What was your academic path like up until joining the CS department?
I graduated from Gyeongnam Science High School in 2 years and entered KAIST in 2004. After graduating with a B.S. in CS, I entered the Master’s program in 2008, and then the Ph.D. program in 2010. I am currently studying under the advisement of Professor Sungeui Yoon.
3) What was your childhood dream? What are you doing now to achieve that dream?
Most children would name a job title when asked what their dream is, but I was different. My childhood dream was to do work which allows as many people as possible to make a living. In retrospect, that dream sounds thoughtful and embarrassing at the same time. I cannot exactly tell you what I am doing not for that dream, but I should work harder to get closer to making it come true.
4) What are your strengths?
I laugh easily. Though, I should probably tell you something that is related to my CS skills: I believe I am good at thinking outside of the box when approaching a given problem. Of course, any idea that comes from outside of the box needs to be validated and is often proven wrong, but a really great idea comes by from time to time.
5) What are you passionately working on in the field of CS these days?
I am currently studying image search, which is about searching an image database for images similar to a given image. More specifically, I am focused on scalable searching techniques which can deal with big database. I am passionate about developing, implementing, and evaluating a more accurate and faster method of image search and presenting it at a top conference.
6) What values and future prospects do you see in your current work?
Currently, most of the online search is based on text, but image searching is expected to gain more attention in the future. The trend is evident in the rapidly increasing number of images in SNS and the Internet, which is made possible by the easy access to images from mobile devices. My current research topic of big data image search is an important issue in this trend, so I am working hard to make contributions.
7) What were your happiest and most disappointing moments, respectively, in the CS department?
My happiest moment was when my first paper in the image search area got accepted at the most renowned conference in the field. It was all the more meaningful, because that was a time when I was feeling unsure about myself, after just having changed my research topic upon becoming a Ph.D. student.
The most disappointing moment was when I found out that a research paper was published on the very topic that I had been working on myself. I was disheartened to find that the contents of the paper, from diagrams to experimental results, were almost exactly the same as mine. I later learned that this sort of event happens often in CS, a field where things progress rapidly. All in all, this is a life of a graduate student whose mood depends on how well the research is going and published.
8) What do you think is the best thing about studying CS?
The field of CS is fast, and that is what I find to be the most attractive about studying it. I always have to stay alert to the rapidly changing trend in order not to get behind. I believe I have the energy to keep up with this field, which also plays very important roles across various domains. What’s more, the validation process of new ideas is also very fast in this field. Paper submission, reviews, and rebuttals happen regularly according to the schedule. I like this academically fast and interactive culture in the field of CS.
9) What would you like to say to those interested in joining the CS department?
Although I do not believe I am at a position to give such advice, I will just say a few personal thoughts on it. As I mentioned above, because CS knowledge evolves fast, what we need is an ability to learn and adapt to new things rather than acquiring bits of knowledge. If you could also have critical thinking and creativity on top of that, it would be great.
10) What are your future plans?
I would first like to express gratitude for this opportunity to participate in the interview. My foremost goal is to earn my Ph.D. degree. I did not decide on specific plans after that, but I am open to continuing my current research and working in the industry.

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Gyeongyeop Lee, MSc. Student Spotlight

1) How did you get to join the Computer Science (CS) department?
I joined the CS department in Fall 2012 as a graduate student.
2) What was your academic path like up until joining the CS department?
I majored in electrical engineering and minored in management science at KAIST.
3) What was your childhood dream? What are you doing now to achieve that dream?
When I was in high school, my dream was to become a math teacher. I eventually chose to major in electrical engineering, because I wanted to work with mobile phones. It sounds abstract, but I have always wanted to do something that directly influences people in a close manner. While keeping that in mind, I worked on developing an English education product for smartphones at a small company named Today’s Word. My job as a project manager at that company involved some programming, which I personally enjoyed a lot. Ultimately, I realized that smartphones are products with strong influence on people’s lives, and I decided to study CS with an aim to maximize the positive side of that influence.
4) What are your strengths?
I love working with kids. There are three ways in which I am still like a kid. First, I am never calculating when I interact with people. Also, I do not worry about things too much, because I have faith that God is always looking out for me in my life. Lastly, there are so many things that I do not know about yet, so I am open to learning new things.
5) What are you passionately working on in the field of CS these days?
I am currently working in the IR&NLP lab and my research involves human languages in the form of text data. More specifically, my research is about searching for bias or falsifications in documents, such as online fake reviews. I have done research which applied past research results from psychology to develop a computer science algorithm. I am working to extend that research, and it is definitely an interesting research experience.
6) What values and future prospects do you see in your current work?
Online reviews are known to heavily influence how people make their purchases. Fake reviews can lead to unfair online transactions which result hurt the customers as well as sellers. Therefore, I believe identifying fake reviews can contribute to the online community by providing a better experience for online shoppers and sellers. In this way, my research dealing with natural language can have positive effects on people in practical ways.
7) What were your happiest and most disappointing moments, respectively, in the CS department?
I enjoy the moments which I am inspired by new ideas for research. Of course, the ideas may get rejected in the end, but I enjoy the whole process of exploring them with my advisor and lab members. I feel more excited when my ideas appear to be clever and actually get implemented to show promising effects.
I remember that my first year as a graduate student had some disappointing moments, when I felt that my CS knowledge was not strong enough due to my background as an EE major.
8) What do you think is the best thing about studying CS?
In my field of study, it is possible to implement new ideas and evaluate them with empirical studies without hardware constraints. I feel lucky to be researching in CS, whenever I hear that experiments take months to do in other departments. Studying CS strengthens problem-solving skills, as we search for better efficiency or effectiveness in our solution. Moreover, CS is attractive in the way that sometimes simple solutions, such as brute-force or rule-based methods, work the best, rather than some complex algorithms.
9) What would you like to say to those interested in joining the CS department?
Many people believe that one must be excellent in programming in order to study CS, but that is not the complete truth. As long as one is passionate about studying CS, programming is something that can be learned over time. Research in CS evolves fast. In order to keep up with the fast pace, it is important to take the coursework seriously and maintain a proactive attitude about learning new things. I recommend to communicate often and effectively with one’s advisor. Lastly, one must be open to use interdisciplinary or integrated approaches when solving a problem in CS.
10) What are your future plans?
I plan to continue my research in fake review and information identification as a Ph.D. student. I am also interested in providing information to users based on their personal text data on websites such as SNS. Another idea that interests me is developing an English writing assistant application for people whose first language is not English. After earning my Ph.D., I would like to become a professor and do research as well as teaching.

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Minjeong Yoo, BSc. Student Spotlight

1) How did you get to join the Computer Science (CS) department?
I had my first encounter with CS in the introduction to programming course during my freshman year of university. I found it fascinating to see robots move on the screen exactly according to the code that I wrote. I especially enjoyed the logical thinking involved in every step of the programming experience, so I chose to major in CS.
2) What was your academic path like up until joining the CS department?
I enjoyed studying mathematics when I was in middle school, so I attended a science high school afterwards and participated in math clubs for several years.
3) What was your childhood dream? What are you doing now to achieve that dream?
It may sound a bit too abstract, but my dream was to become a great leader. I have not achieved that dream in significant ways yet. However, I believe that studying and working diligently in my field of choice, CS, will lead to making that dream come true eventually.
4) What are your strengths?
My strength is that when I set a goal, I am very persistent in making sure that I achieve it.
5) What are you passionately working on in the field of CS these days?
6) What values and future prospects do you see in your current work?
Currently, there is a shortage of people with science and technology background in the area of national policy making. Thus, I would like to utilize my CS background to create effective policies for advancement of science and technology in Korea.
7) What were your happiest and most disappointing moments, respectively, in the CS department?
My happiest moment is when I finished my first project. It gave me the confidence that I much needed at the time, when I had just joined the CS department and was worried about my lack of skills. After finishing that project perfectly by myself, however, I was simply happy and felt more confident about my potential to excel in this field.
8) What do you think is the best thing about studying CS?
Studying CS develops logical thinking skills, and putting new ideas into action is possible by writing code and implementing prototypes.
9) What would you like to say to those interested in joining the CS department?
People tend to be shy about not knowing enough when they come to the CS department and begin learning CS in depth for the first time. I would tell them not to be shy about asking questions to friends or upperclassmen whenever they feel stuck on something. Asking questions and discussing problems will surely lead to better thinking and programming skills.
10) What are your future plans?
After earning my degree, I would like to work for a government agency and work hard to make national policies that foster science and technology advancement in Korea.

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Huiseok Son, PhD Student Spotlight

1) How did you get to join the Computer Science (CS) department?
My choice to join the CS department was, to be sure, a surprising one. When I was in high school, I was just a regular student who liked math and chemistry and knew nothing about programming. That was probably the reason why I did not receive a good grade from the required programming course here at KAIST. It left me feeling that my programming skills are rather inferior compared to those of my peers. On a fateful Teacher Appreciation Day, however, the adviser of my club told me something that changed my perspective. He encouraged me to apply to the Department if what I want to do in my future career is closely related to computer science. This advice motivated me to study harder during summer breaks, and when the time to apply for the Department came, I took the chance and chose the CS department.
2) What was your academic path like up until joining the CS department?
I did not have any special academic path until I came to the Department. As I said above, I was just a regular high school student who studied hard according to the given curriculum, and after I came to university, I actively participated in the campus life. I motivated myself to work harder in order to stay competitive amongst my bright peers. As a result, my grades improved quite a lot during those times.
3) What was your childhood dream? What are you doing now to achieve that dream?
My early childhood dream was to go to Harvard University, which is a very simple-minded and wistful dream in retrospect. I did not even know what I wanted to major in but just wanted to go the world’s best university. But, as I grew up, I found myself to be the happiest and passionate when I was passing on my knowledge to others. It led me to consider a teaching profession, so I now want to become a university professor. Since that dream took place within my mind, I have always asked myself if I will ever be knowledgeable enough to teach people at university level. That question humbles me and motivates me to work harder in my studies and research. I am also open to meeting and learning from people of diverse backgrounds.
4) What are your strengths?
My strengths are my optimistic personality and healthy body. I never let go of optimistic thinking regardless of what circumstances I may find myself in. Such optimism has helped me reduce stress even at times of heavy workloads. I also believe that optimistic thinking often leads to wisdom that allows me to overcome the present hardship. My healthy body is a result of the regular exercise I have enjoyed doing since I was a child. Even now, when I feel stressed out, I would go out to exercise with my friends. Physical strength is an essential factor in one’s ability to do research.
5) What are you passionately working on in the field of CS these days?
I am currently working at a laboratory, so I am working hard on the given projects as well as my individual research. I am eager to produce good results with my research soon and go to top conferences and get published on journals. What I really like about going to conferences is talking to researchers from other countries. I find such conversations to be academically enriching and fun！
6) What values and future prospects do you see in your current work?
My current research has to do with smartphones and their user experiences. Thus, if I can produce good results, it would help to alleviate some of the inconveniences that people feel while using their smartphones. Furthermore, if I can pass on the lessons from my current research experience to the future generation, that would be even more valuable of a contribution.
7) What were your happiest and most disappointing moments, respectively, in the CS department?
Like most of the CS students, I had my happiest moment when I see that my program is working correctly after locating and fixing a bug after countless hours. Nothing can really compare to that moment of joy, which usually leads me to shout out “Hurray！”
The most disappointing moment was when I got my conference paper rejected. Receiving cold reviews on a paper that I carefully composed can be hard to take. It is a humbling experience, but it also strengthens my desire to write better papers and get accepted to top conferences.
8) What do you think is the best thing about studying CS?
The best thing is that the people I meet in this field tend to be very open-mined and practical. It is hard to find working environments that are freer than they are for CS-related jobs. People who study CS are always open to learning new things. The fact that computers are ubiquitous in today’s world means that there is more need for people who study CS like me. I find it highly attractive that CS is a field with a vast amount of opportunity to make a difference in the world.
9) What would you like to say to those interested in joining the CS department?
I am sure that you are making a great choice for the present as well as the future！ This is a field that never gets boring and always presents new challenges. I would also like to tell those who are afraid of joining the CS department, that it may very well be worth a try. CS is a field of study with a relatively high learning curve at first, but after you open your eyes to all that it has to offer, it is truly an amazing experience. I am personally an example of someone who could not even program to print out “Hello World” during my freshman year, but now happily working on my Ph.D.. So, can your program print out “Hello World?” Then, I would say that you are at a better starting position than where I was.
10) What are your future plans?
I want to publish outstanding papers and earn my Ph.D. degree. Although I am not sure where I will be working at afterwards, I do want to spend some time studying in the United States. I want to study in the States, where the best of minds in CS gather to develop and share their ideas, so that I could become a great researcher and professor myself. It is okay if I end up doing with a job other than being a professor, though, as long as I am always learning and improving myself as a person.

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Prof. Kyu­Young Whang Receives Contributions Award..

Prof. Kyu-Young Whang, Distinguished Professor of Computer Science at KAIST, was the recipient of the 2014 ACM SIGMOND Contributions Award.
Founded in 1947, the Association for Computing Machinery (ACM) is the world’s largest educational and scientific computing society, delivering resources that advance computing as a science and profession.
SIGMOD is the Association for Computing Machinery’s Special Interest Group on Management of Data, which specializes in large-scale data management problems and databases.
Since 1992, the ACM SIGMOND has presented the contributions award to one scientist who has made significant contributions to the field of database systems through research funding, education, and professional services. So far, 23 people including Professor Whang have received the award.
Professor Whang was recognized for his key role in the growth of international conferences and journals in the field of database such as The VLDB Journal (The International Journal on Very Large Data Bases), VLDB Endowment Inc., IEEE Technical Committee on Data Engineering, and Database Systems for Advanced Applications (DASFAA). IEEE stands for the Institute of Electrical and Electronics Engineering.
For the full list of ACM SIGMOND Contributions Award recipients, please go to
http://www.sigmod.org/sigmod-awards/sigmod-awards#contributions

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Prof. Min H. Kim is appointed as an Associate Edit..

Prof. Min H. Kim is appointed as an Associate Editor of ACM Transactions on Graphics (TOG).
The Association for Computing Machinery (ACM) was founded in 1947 and has served as the world’s most prestigious scientific and educational computing society along with the Institute of Electrical and Electronics Engineers (IEEE).
The roles and responsibilities of an Associate Editor include selecting appropriate referees to perform reviews on submitted manuscripts and preparing reports for the main findings of the review process. The manuscripts selected for publication are presented at the world’s largest Computer Graphics conference, ACM SIGGRAPH.
Professor Kim has published numerous papers in the areas of computer graphics research, with emphases in the areas of 3D imaging spectroscopy and visual perception. He regards his appointment to TOC as a great opportunity and looks forward to making further outstanding contributions to advance research in computing.

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Eugen Wüster Prize Award

[Prof. Key­Sun Choi] At the closing ceremony of the International Conference in Terminology and Knowledge Engineering (TKE) 2014 hosted by the German Institute for Standardization in Berlin, Germany, Professor Key-Sun Choi of Department of Computer Science and Korea Terminology Research Center for Language and Knowledge Engineering (KORTERM) at KAIST has been awarded the Eugen Wüster Prize for his long-time international achievements in the field of terminology science as the Secretary of ISO/TC37/SC4 for language resource management and the Vice-President of Infoterm since 2002.
The Prize named in honour of Eugen Wüster (1898-1977), commonly known as the “Father of Terminology Science”, is being awarded every three years from 1997, to recognize scholars of outstanding achievements in the field of terminology science and other related studies. So far, a total number of 10 scholars around the world, including Prof. Choi, have received the Award.
For further information, please visit http://www.infoterm.info/activities/news/2014/2014_07_06.php.

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Developing a Text Mining Search Engine for Cancer ..

[Prof. Jong Cheol Park]
The Ministry of Science, ICT, and Future Planning announced on May 22nd that the research teams led by Professor Jong Cheol Park of KAIST and Professor Hyunju Lee of GIST have developed OncoSearch, a text mining search engine that searches Medline abstracts for sentences describing gene expression changes in cancers.
This federally funded research project was carried out on an interdisciplinary research effort converging linguistics, computer engineering, biology, and medicines.
In order to identify genes that cause cancers and to understand how such genes affect cancers, abnormal gene expressions in cancers are actively studied. To facilitate the studies, OncoSearch utilizes powerful text mining techniques to extract the relevant information from the large amount of information available in the biomedical literature. OncoSearch allows the user to efficiently search for genes that affect particular types of cancers, compare expression levels of a gene across various types of cancers, and explore a graph to find interactions between genes in a type of cancer.
“OncoSearch is a novel tool that automatically collects information on cancer related genes using the latest text mining techniques, and we expect its active use will help the ongoing cancer research efforts,” said Professor Park.
The research results were published in the online version of Nucleic Acids Research, on May 9th, 2014.